Technologies to monitor websites visit data are adopted to analyze and further, optimize the internet performance. Such technologies include data monitoring, data collection, data analysis, and data reporting, etc. The operation efficiency and visit traffic of a website can be improved using the tracked and analyzed data, and the functional goals that a website developer expects can be achieved.
The current technology collects statistic data of a website that includes numbers of page views (PV) and numbers of unique visitors (UV).
PV is a major criterion to measure a website, a news link of a website, and traffic of a website. Monitoring the varying trend of the website PV and analyzing the reasons for the varying trend is regular work for many website administrators. The word “page” in the term “page views” generally refers to an ordinary html page, but may also refer to html contents dynamically-generated by php, jsp, etc. An html content request from a browser may be considered to be a PV, which is accumulated into a sum of PV.
UV refers to human beings that access and browse a webpage via internet. For example, user A opens the homepage of a certain website, and registers as a member on a computer. A moment later, user B registers as another member using the same computer. As user A and user B use the same computer with the same IP address. An official counter of the website records login information from a single IP address. However, a further monitoring system may determine the number of actual users according to other conditions. Further, a website developer can get accurate and complete information of the users of the website. For instance, using the information of registered users, different computers sharing an IP address in an internet café or a computer room can be distinguished.
The current technologies utilize a big data platform to monitor and analyze websites. Visit data of websites are collected on a daily basis, and daily visit effect data including PVs and UVs are calculated. However, the big data platform requires centralized computation of the daily collected data, and thus, requires high performance computers. Further, processing a large amount of data daily is inefficient. In view of the foregoing, it is difficult for the current technologies to provide real-time monitoring and analysis of the website visit data from various perspective views, for instance, real-time PVs and UVs calculated based on visit traffic and visit source, etc.